International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 7 Issue 6
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A Hierarchical Adaptive Energy-Efficient Resource Allocation Management Framework for Multi-Tier IoT–Fog Computing Environment Using Real-World Datasets

Author(s) Mr. Kotari Suresh, Prof. Dr. M. Humera Khanam
Country India
Abstract One of the models of the resources allocation presented in the paper is one model of framework that can be applied in multi-tier Internet of Things (IoT)-Fog-Cloud computing frameworks, called Hierarchical Adaptive Energy-Efficient Resource Allocation and Management (AEERAM-RE). The resource allocation in the system is dynamically performed to have the opportunity to balance the computational load, energy consumption as well as the QoS in the case of heterogeneous and varying working loads. Adaptive energy-efficiency, multi objective optimization, alternative energy sources (solar /wind) and integrated security module (ResA-D2PySepCo) are all controlled by one structure. The model of the AEERAM-RE is proved to be applicable in the context of measuring the specific key measures related to the IoT based on the actual data on the IoT (Multi-Tier IoT Resources management, ToN-IoT, Edge-IIoT, CICIDS2018 dataset, UNSW-NB15). As it is stated in findings, intelligent management of distribution of resources, renewable integration and multi-objective optimization are the major contributors to make the grid rely on minimization grid dependency, utilize the fog node to its maximum and be sustainable.
Keywords Keywords: Internet of Things, Fog Computing, Adaptive Energy-Efficiency, Multi-Objective Optimization, Resource Allocation, Resource Management, Cyber Security
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-29
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.60750
Short DOI https://doi.org/hbdrdk
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